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pegasus-xsum_summarization
This model is a fine-tuned version of google/pegasus-xsum on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.7876
- Rouge1: 25.7148
- Rouge2: 10.9685
- Rougel: 21.6394
- Rougelsum: 22.3122
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5.6e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|---|---|---|---|---|---|---|---|
| 1.633 | 1.0 | 50 | 1.8839 | 24.9703 | 9.6517 | 19.9759 | 21.088 |
| 1.3917 | 2.0 | 100 | 1.8565 | 24.4395 | 9.1755 | 19.5702 | 20.5489 |
| 1.2576 | 3.0 | 150 | 1.8361 | 24.8266 | 10.2009 | 20.074 | 21.382 |
| 1.1191 | 4.0 | 200 | 1.8226 | 25.9635 | 11.7704 | 21.7787 | 22.365 |
| 1.1138 | 5.0 | 250 | 1.8239 | 26.7874 | 12.2832 | 22.7792 | 23.4501 |
| 1.0338 | 6.0 | 300 | 1.8094 | 26.3543 | 12.0501 | 22.3172 | 23.1194 |
| 1.0084 | 7.0 | 350 | 1.7923 | 25.5686 | 11.0213 | 21.5288 | 21.8892 |
| 1.0098 | 8.0 | 400 | 1.7876 | 25.7148 | 10.9685 | 21.6394 | 22.3122 |
Framework versions
- Transformers 4.20.1
- Pytorch 1.12.0
- Datasets 2.3.2
- Tokenizers 0.12.1
